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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Correlating activities and defects in (photo)electrocatalysts using in-situ multi-modal microscopic imaging

Photo(electro)catalysts use sunlight to drive chemical reactions such as water splitting. A major factor limiting photocatalyst development is physicochemical heterogeneity which leads to spatially dependent reactivity. To link structure and function in such systems, simultaneous probing of the electrochemical environment at microscopic length scales and a broad range of timescales (ns to s) is required. Here, we address this challenge by developing and applying in- situ (optical) microscopies to map and correlate local electrochemical activity, with hole lifetimes, oxygen vacancy concentrations and photoelectrode crystal structure. Using this multi-modal approach, we study prototypical hematite (α-Fe 2 O 3 ) photoelectrodes. We demonstrate that regions of α-Fe 2 O 3 , adjacent to microstructural cracks have a better photoelectrochemical response and reduced back electron recombination due to an optimal oxygen vacancy concentration, with the film thickness and extended light exposure also influencing local activity. Our work highlights the importance of microscopic mapping to understand activity, in even seemingly homogeneous photoelectrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Future directions for active matter on ordered substrates

Active matter is a term encompassing particle-based assemblies with some form of self-propulsion, including certain biological systems as well as synthetic systems such as artificial colloidal swimmers, all of which can exhibit a remarkable variety of new kinds of nonequilibrium phenomena. A wealth of non-active condensed matter systems can be described in terms of a collection of particles coupled to periodic substrates, leading to the emergence of commensurate-incommensurate effects, Mott phases, tribology effects, and pattern formation. It is natural to ask how such phases are modified when the system is active. Here we provide an overview and future directions for studying individual and collectively interacting active matter particles coupled to periodic substrates, where new types of commensuration effects, directional locking, and active phases can occur. Importantly, further directions for exploration include directional locking effects, the realization of active solitons or active defects in incommensurate phases, active Mott phases, active artificial spin ice, active doping transitions, active floating phases, active surface physics, active matter time crystals, and active tribology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗
DOE OSTI2020

Thermal conductance enhanced via inelastic phonon transport by atomic vacancies at Cu/Si interfaces

Understanding and controlling heat transfer across interfaces has become an important issue for the performance of micro- and nanoscale electronics, as well as achieving a high figure of merit for thermoelectrics. Intrinsic and extrinsic defects can have a significant impact on thermal transport in bulk materials and across interfaces, but the mechanism is not well understood. Here, nonequilibrium molecular dynamics simulations are used to determine the impact of interfacial atomic vacancies on thermal transport across a Cu/Si junction. In contrast to the reduction in thermal transport typically seen with bulk defects, we find that by introducing atomic vacancies at a concentration of 6.3% near the interface in either or both materials, the interfacial thermal conductance can be increased by up to 76%. By controlling the initial positions of the vacancies and keeping track of their movements and population, we find that interfacial thermal transport is dependent on temperature, vacancy concentration, and distribution, and a positive correlation between the conductance and point defect activities (extent of vacancy migration, rate of Frenkel defect creation and annihilation) is observed. Further calculations based on the phonon density of states and normal mode decomposition reveal that the increase in interfacial thermal conductance originates primarily from high-frequency phonons, supported by enhanced inelastic phonon transport which contributes to more than 60% of the increase. Our findings suggest a practical way to manipulate inelastic phonon conversion through the presence of defects, which provides an alternative perspective on improving thermal transport between materials with a large lattice mismatch.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Mechanochemical topological defects in an active nematic

We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±$\frac{1}{2}$ defects. The enabling term is analogous to polarization charge density seen in dielectric materials. We demonstrate the ability of this system to identify defects in both passive and active nematics. Our results illustrate that a relatively simple feedback scheme, expressed as a system of partial differential equations, is capable of producing chemical signals in response to inherently nonlocal structures in anisotropic media. Here, we posit that such coarse-grained systems can help generate testable hypotheses for regulated processes in biological systems, such as morphogenesis, and motivate the creation of bio-inspired materials that utilize dynamic coupling between nematic structure and biochemistry.

42 ENGINEERING↗
DOE OSTI2021

Defect Spirograph: Dynamical Behavior of Defects in Spatially Patterned Active Nematics

We report that topological defects in active liquid crystals can be confined by introducing gradients of activity. Here, we examine the dynamical behavior of two defects confined by a sharp gradient of activity that separates an active circular region and a surrounding passive nematic material. Continuum simulations are used to explain how the interplay among energy injection into the system, hydrodynamic interactions, and frictional forces governs the dynamics of topologically required self-propelling + 1/2 defects. Our findings are rationalized in terms of a phase diagram for the dynamical response of defects in terms of activity and frictional damping strength. Different regions of the underlying phase diagram correspond to distinct dynamical modes, namely immobile defects, steady rotation of defects, bouncing defects, bouncing-cruising defects, dancing defects, and multiple defects with irregular dynamics. These dynamic states raise the prospect of generating synchronized defect arrays for microfluidic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Locally Engineering and Interrogating the Photoelectrochemical Behavior of Defects in Transition Metal Dichalcogenides

Transition metal dichalcogenides (TMDs) are attractive materials for a variety of applications in solar energy conversion and electrocatalysis, due to their favorable optical and electrical properties and their unique two-dimensional structures which facilitate the fabrication of wide-area, ultrathin layers. Unfortunately, the basal planes which make up the majority of these materials are relatively inert, and thus a great deal of effort has been directed to engineering favorable, catalytically active defects into these materials. In this paper, we demonstrate how probe-based electrochemical techniques can be employed as multifunctional tools for locally modifying TMD materials and probing the electrochemical behavior of the resulting defects. Scanning Electrochemical Cell Microscopy (SECCM) was employed to locally anodize exfoliated p-type WSe 2 nanosheets, creating hole-like defects within individual basal planes in a highly controllable fashion. Photoelectrochemical SECCM imaging was then employed to characterize the chemical behavior of these engineered defects, revealing significantly enhanced activity toward the Hydrogen Evolution Reaction (HER). Atomic force microscopy studies are presented which suggest these enhancements result from an increased density of monolayer-high step features within the anodized defects. Analysis of the SECCM data in the context of finite element simulations revealed that these enhancements increased with increasing anodization time, with local kinetic rates over 2 orders of magnitude higher than unaltered basal planes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unlocking Mesoscopic Disorder in Graphitic Carbon with Spectroelectrochemistry

Intrinsic structural and oxidic defects activate graphitic carbon electrodes towards electrochemical reactions underpinning energy conversion and storage technologies. Yet, these defects can also disrupt the long-range and periodic arrangement of carbon atoms, thus, the characterization of graphitic carbon electrodes necessitates in-situ atomistic differentiation of graphitic regions from mesoscopic bulk disorder. Here, we leverage the combined techniques of in-situ attenuated total reflectance infrared spectroscopy and first-principles calculations to reveal that graphitic carbon electrodes exhibit electric-field dependent infrared activity that is sensitive to the bulk mesoscopic intrinsic disorder. With this platform, we identify graphitic regions from amorphous domains by discovering that they demonstrate opposing electric-field-dependent infrared activity under electrochemical conditions. Our work provides a roadmap for identifying mesoscopic disorder in bulk carbon materials under potential bias.

Disordered graphitic carbon electrodes↗
DOE OSTI2022

Effect of oxide layer growth conditions on radiation detection performance of Ni/SiO 2 /epi-4H-SiC MOS capacitors

We report high resolution radiation detection has been demonstrated using Ni/SiO2/n-4H-SiC metal-oxidesemiconductor vertical capacitors fabricated using highly crystalline 4H-SiC epilayers. The oxide layers have been grown thermally using two different approaches: i) in-air, and ii) oxygen-ambience oxidation. The devices fabricated using the former method exhibited dark currents one order of magnitude higher than that in the latter. The observed difference has been attributed to the back-contact series resistance and capacitance. Regardless of the difference in the device parameters, detectors prepared using both of the methods exhibited very high energy resolutions of ≤ 0.5% for 5486 keV alpha particles emitted by an 241Am radioisotope. Capacitance mode deep level transient spectroscopic (DLTS) studies revealed similar type of electrically active defects along with Z1/2 and EH5 deep level defects in both the types of devices. The DLTS scans also revealed positive polarity peaks in these devices which indicate emission from minority carrier trap centers. The activation energy corresponding to the peak was found to be ~1.2 eV which has been assigned to HK3 defects responsible for hole trapping in 4H-SiC. The possibility of appearance of the positive peak due to non-negligible impedance of the back-contact has been ruled out based on the observation that the centroid of the observed peak did not change with detectors having different device parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Strain-graded quantum dots with spectrally pure, stable and polarized emission

Structural deformation modifies the bandgap, exciton fine structure and phonon energy of semiconductors, providing an additional knob to control their optical properties. The impact can be exploited in colloidal semiconductor quantum dots (QDs), wherein structural stresses can be imposed in three dimensions while defect formation is suppressed by controlling surface growth kinetics. Yet, the control over the structural deformation of QDs free from optically active defects has not been reached. Here, we demonstrate strain-graded CdSe-ZnSe core-shell QDs with compositionally abrupt interface by the coherent pseudomorphic heteroepitaxy. Resulting QDs tolerate mutual elastic deformation of varying magnitudes at the interface with high structural fidelity, allowing for spectrally stable and pure emission of photons at accelerated rates with near unity luminescence efficiency. We capitalize on the asymmetric strain effect together with the quantum confinement effect to expand emission envelope of QDs spanning the entire visible region and exemplify their use in photonic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Defect passivation of perovskites in high efficiency solar cells

Abstract Metal halide perovskite solar cells (PSCs) have enormous potential as the next-generation photovoltaic technology. Being solution-processed at relatively low temperatures, it is inevitable that crystallographic defects are formed in abundance during fabrication. Such defects may cause undesirable energy losses by non-radiative recombination to limit the performance of PSCs. More importantly, it has become apparent that defect activity is fundamentally responsible for the operational instability issues hindering the commercialization readiness of PSCs. It is therefore necessary to develop strategies to minimize defect formation and to passivate formed defects. Here, we discuss recent advances on such defect mitigation and passivation strategies. We especially emphasize on methodologies that are incorporated into state-of-the-art PSCs that have demonstrated world record efficiencies and long-term stability.

14 SOLAR ENERGY↗
DOE OSTI2020

Influence of Charge Transport Layers on Capacitance Measured in Halide Perovskite Solar Cells

Capacitance-based techniques were previously used to measure the electrical properties of halide perovskite solar cells (PSCs) such as defect activation energy and density, carrier concentration, and dielectric constant, which provide key information for evaluating the device performance. Herein, we show that capacitance-based techniques cannot be used to reliably analyze the properties of defects in the perovskite layer or at its interface, since the high-frequency capacitance signature is due to the response of charge carriers in the hole-transport layer (HTL). For HTL-free PSCs, the high-frequency capacitance can be considered as the geometric capacitance for analyzing the dielectric constant of the perovskite layer, since there is no trapping and de-trapping of charge carriers in the perovskite layer. We also find that the low-frequency capacitance signature can be used to calculate the activation energy of the ionic conductivity of the perovskite layer, but the overlapping effects with charge transport materials must be avoided.

14 SOLAR ENERGY↗
DOE OSTI2024

Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach

Here, the relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe 35+ irradiation is systematically investigated, employing experimental characterizations combined with first-principle calculations. Based on the ion irradiation-induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗
DOE OSTI2023

Hydrogen-induced degradation dynamics in silicon heterojunction solar cells via machine learning

Abstract Among silicon-based solar cells, heterojunction cells hold the world efficiency record. However, their market acceptance is hindered by an initial 0.5% per year degradation of their open circuit voltage which doubles the overall cell degradation rate. Here, we study the performance degradation of crystalline-Si/amorphous-Si:H heterojunction stacks. First, we experimentally measure the interface defect density over a year, the primary driver of the degradation. Second, we develop SolDeg, a multiscale, hierarchical simulator to analyze this degradation by combining Machine Learning, Molecular Dynamics, Density Functional Theory, and Nudged Elastic Band methods with analytical modeling. We discover that the chemical potential for mobile hydrogen develops a gradient, forcing the hydrogen to drift from the interface, leaving behind recombination-active defects. We find quantitative correspondence between the calculated and experimentally determined defect generation dynamics. Finally, we propose a reversed Si-density gradient architecture for the amorphous-Si:H layer that promises to reduce the initial open circuit voltage degradation from 0.5% per year to 0.1% per year.

14 SOLAR ENERGY↗
DOE OSTI2024

Predicting Thermochemical Equilibria with Interacting Defects: Sr 1 − x Ce x Mn O 3 − δ Alloys for Water Splitting

Solar thermochemical hydrogen is one of the few potential routes towards direct fuel production from renewable energy sources, but the thermodynamic boundary conditions for efficient and economic energy conversion are challenging. Success or failure of a given oxide working material depends on the subtle balance between enthalpy and entropy contributions in the redox processes. Developing a mechanistic understanding of the behavior of materials on the basis of atomistic models and first-principles calculations is an important part of advancing the technology. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox-active defects start to interact with each other, thereby impeding the formation of additional defects. This problem is of more general importance to applications that rely on high levels of off-stoichiometry or doping, including, for example, batteries, thermoelectrics, and ceramic fuel cells. To account for such repulsive defect interactions, we introduce a statistical mechanics approach, defining an expression for the free energy of defect interaction based on limited sampling of defect configurations in density functional theory supercell calculations. The parameterization of this energy contribution as a function of defect concentration and temperature allows on-the-fly simulation of thermochemical equilibria. The approach consistently incorporates finite temperature effects by including the leading contributions to the temperature-dependent free energy for the case at hand, i.e., the ideal gas and configurational enthalpies and entropies. We demonstrate the capability and utility of the approach by simulating the water splitting redox processes for Sr 1 − x Ce x Mn O 3 − δ alloys. Published by the American Physical Society 2024

08 HYDROGEN↗
DOE OSTI2026

Radiative Defects in Chloride-Activated CdSe Thin Films

Defect recombination limits wide-gap Se-based chalcogenide devices, yet how chloride activation reshapes radiative pathways remains unclear. Here we show that a 40 min CdCl 2 anneal converts evaporated CdSe from porous nanograins into dense micrometer-scale polycrystals and sharpens the optical band edge, reducing the Urbach energy from 85 to 17 meV at 300 K. Combining temperature- and fluence-dependent photoluminescence (PL), time-resolved PL, hyperspectral mapping, and hybrid-DFT, we resolve three emissive channels and identify their mechanisms. The near-edge band is excitonic at low temperature and evolves into free-carrier emission at elevated temperature. A sub-gap band at E g −0.45 eV requires above-gap carriers and thermally quenches with a 0.16 eV activation energy. A broad ∼1.05 eV infrared band is excited by above- and below-gap photons and retains microsecond lifetimes at room temperature; patial mapping links it to edge-rich microstructure. Calculations suggest selenium-vacancy and cadmium-vacancy−chlorine complexes, pointing to routes to suppress defect-related losses in wide-gap chalcogenide devices.

Abudulimu, Abasi [Univ. of Toledo, OH (United Stat↗